Cooperation on capacitated inventory situations with fixed holding costs

[Abstract] In this paper we analyze a situation in which several firms deal with inventory problems concerning the same type of product. We consider that each firm uses its limited capacity warehouse for storing purposes and that it faces an economic order quantity model where storage costs are irrelevant (and assumed to be zero) and shortages are allowed. In this setting, we show that firms can save costs by placing joint orders and obtain an optimal order policy for the firms. Besides, we identify an associated class of costs games which we show to be concave. Finally, we introduce and study a rule to share the costs among the firms which provides core allocations and can be easily computed.Ministerio de Ciencia e Innovación; MTM2011-23205Galicia. Consellería de Economía e Industria; INCITE09-207-064-PRComunidad Valenciana. Generalidad; ACOMP/2014Ministerio de Ciencia e Innovación; MTM2011-27731-C0

Unitary Owen Points in Cooperative Lot-Sizing Models with Backlogging

This paper analyzes cost sharing in uncapacitated lot-sizing models with backlogging and heterogeneous costs. It is assumed that several firms participate in a consortium aiming at satisfying their demand over the planning horizon with minimal operating cost. Each individual firm has its own ordering channel and holding technology, but cooperation with other firms consists in sharing that information. Therefore, the firms that cooperate can use the best ordering channels and holding technology among members of the consortium. This mode of cooperation is stable. in that allocations of the overall operating cost exist, so that no group of agents benefit from leaving the consortium. Our contribution in the current paper is to present a new family of cost sharing allocations with good properties for enforcing cooperation: the unitary Owen points. Necessary and sufficient conditions are provided for the unitary Owen points to belong to the core of the cooperative game. In addition, we provide empirical evidence, through simulation, showing that, in randomly-generated situations, the above condition is fulfilled in 99% of the cases. Additionally, a relationship between lot-sizing games and a certain family of production-inventory games, through Owen’s points of the latter, is described. This interesting relationship enables easily constructing a variety of coalitionally stable allocations for cooperative lot-sizing models.The research authors is supported from Spain’s Ministerio de Ciencia, Innovación y Universidades (MCIU), from the Agencia Estatal de Investigación (AEI) and from the Fondo Europeo de Desarrollo Regional (FEDER) under the projects MTM2016-74983-C02-01 and PGC2018-097965-B-I00. The research of the third author is also partially supported from projects FEDER-US-1256951, CEI-3-FQM331 and NetmeetData: Ayudas Fundación BBVA a equipos de investigación científica 2019

A collaborative framework in outbound logistics for the us automakers

The competitive landscape of the U.S. automotive market has transformed from the traditional Big Three players to too many viable players. In 2008-2009, the harsh market conditions, excess production capacity, capital asset redundancies, and many inefficient strategies submerged as the roadblocks for the US automakers to stay competitive and profitable in the North American market. In this new competitive era, cross-company collaboration in product development, standardizing and communizing supply base, sharing flexible manufacturing platforms, using common inbound and out bound logistics service providers and warehousing etc. can play vital roles for the US automakers to reduce overall cost and return to profitability. Through the horizontal collaboration in the outbound logistics operations, these companies can create close-knit business partnership and act faster than the foreign rivals in delivering finished vehicles at the optimum cost. The optimization of outbound logistics operations through consolidation and collaboration among OEMs has tremendous potential to contribute to the profitability by lowering the cost of transportation, in-house inventory, transportation time, and facility costs. The collaboration in the intra- and inter-OEM outbound logistics operations is a critical area that the US automakers need to pay attention and prioritize in their cost reduction initiatives. This research presents an integrated collaboration framework for the outbound logistics operations of the US automakers. In our framework, we propose three potential levels for the US automakers to form outbound logistics collaboration: operational, tactical, and strategic. Our research proposition is to improve the performance of outbound logistics systems of automotive OEMs by means of horizontal collaboration between plants and competing OEMs. The proposed research thus relates to the literature on logistics system design and management and horizontal collaboration in supply chain management. The collaboration framework is demonstrated through a real world case study in US automotive industry. The contribution of this research is the introduction of a framework for intra- and inter-OEM collaboration and the development of novel logistics network design and flow models integrated with inventory models, lost sales, and expedited shipment. Besides the contribution to the academic literature, the proposed collaborative distribution system is a new concept in the automotive industry. Hence, this novel research work will also benefit to the practitioners. Keywords: Operational Collaboration, Tactical Collaboration, Strategic Collaboration, Frequency based Inventory, Customer Patience and Lost Sales, Expedited Shipments

Optimal capacity in a coordinated supply chain

We consider a supply chain in which a retailer faces a stochastic demand, incurs backorder and inventory holding costs and uses a periodic review system to place orders from a manufacturer. The manufacturer must fill the entire order. The manufacturer incurs costs of overtime and undertime if the order deviates from the planned production capacity. We determine the optimal capacity for the manufacturer in case there is no coordination with the retailer as well as in case there is full coordination with the retailer. When there is no coordination the optimal capacity for the manufacturer is found by solving a newsvendor problem. When there is coordination, we present a dynamic programming formulation and establish that the optimal ordering policy for the retailer is characterized by two parameters. The optimal coordinated capacity for the manufacturer can then be obtained by solving a nonlinear programming problem. We present an efficient exact algorithm and a heuristic algorithm for computing the manufacturer's capacity. We discuss the impact of coordination on the supply chain cost as well as on the manufacturer's capacity. We also identify the situations in which coordination is most beneficial. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58030/1/20271_ftp.pd

Estimation and Allocation of Cost Savings from Collaborations

학위논문(석사) -- 서울대학교대학원 : 공과대학 산업공학과, 2021.8. 문일경.The physical internet (PI) is a state-of-the-art open global supply chain network that is gaining attention from both participants and researchers of supply chains. The PI uses standardized containers to dispatch shipments through an interconnected network within a supply chain, where information, storage facilities, and transportation methods are shared participants of the physical internet. The network aims to save costs, handle volatile demand and information, and be socially and environmentally responsible. Up until now, however, almost all studies concerning the PI have focused primarily on its conceptual development and the advantages of putting it into practical, widespread use. Studies that consider realistic constraints of its use, such as empty runs of transportation, limited capacity of resources, or an equitable allocation of the cost savings obtained from its implementation are limited. While in general the PI can offer greater efficiency and sustainability compared to the traditional supply chain network, in certain situations some users of it experience loss through its use because of the inherent setup it presents of sharing capacitated resources. Therefore, compensating companies that experience loss when joining a PI is essential in building a solid network. In this thesis, in order to address the minimization of a total cost problem in the production-inventory-distribution decision of a PI, we first propose a mixed-integer linear programming (MILP) model formulation that takes into account capacitated factory and warehouse capacity, the penalty sustained by empty runs of transportation, and the maximum delivery distance of freight runs. Next, we use the model to compare the costs incurred by individual players when they do not participate in the PI and the costs of collaboration in the PI in which players do participate. After comparing the costs saved by participating in the PI, we then allocated the cost savings among independent supply chains, allotting them through three different allocation methods, including the Shapley value method, which is a cooperative game theory solution method.피지컬 인터넷은 최첨단의 공유 글로벌 공급망 네트워크로 다양한 학자 및 실무자들의 관심을 끌고 있습니다. 피지컬 인터넷은 표준화된 컨테이너를 이용하여 상호 연결된 네트워크를 통해 제품 및 재화를 발송합니다. 이 때, 정보, 보관 시설 및 운송 수단은 참여자들 간에 공유됩니다. 이 네트워크는 비용을 절감하고 변동성이 큰 수요와 정보를 처리하고 사회적, 환경적으로 지속가능성을 유지하는 것을 목표로 합니다. 지금까지 피지컬 인터넷에 대한 연구는 주로 그 개념과 프레임워크의 개발, 그리고 사회에 도입하였을 때의 장점을 주로 다루었습니다. 피지컬 인터넷 속에서 운송 수단의 공차 운행, 자원의 한계 용량, 절감한 비용의 배분 등과 같은 현실적인 요소들에 대한 고려를 한 연구들은 아직 제한적입니다. 피지컬 인터넷은 전체적으로 보았을 때 기존의 공급망에 비해 더 큰 효율성과 지속 가능성을 얻을 수 있지만 특정한 상황에서는 일부 참가자는 현실적인 제약 상황으로 인해 오히려 손해를 보는 경우가 존재할 수 있습니다. 따라서 더 큰 효율성과 지속 가능성을 얻을 수 있는 피지컬 인터넷에 기업들을 참여시키기 위해선 그들이 참여함으로써 손해를 보는 상황을 만들지 않는 것이 필수적인 조건입니다. 본 논문에서는 먼저 운송 수단의 공차 운행 페널티 비용, 최대 운송 가능 거리, 창고의 폐쇄를 고려한 통합 생산-재고-물류 최소 비용 혼합 정수 선형 계획법 모형을 제안하였습니다. 그 후, 개별적인 공급망의 비용과 피지컬 인터넷 하에서 협업한 통합 공급망의 비용을 비교하여 비용 절감 효과를 계산한 후 협력 게임의 일종인 섀플리 값을 포함한 세 가지 배분 방법을 통해 비용 절감 효과 배분을 살펴보았습니다.Chapter 1 Introduction 1 Chapter 2 Literature Review 5 2.1 The Physical Internet 5 2.2 Cost Savings Allocation Problem 8 Chapter 3 Model Formulation 10 3.1 Problem Definition 10 3.2 Assumptions 15 3.3 Notaions and Formulations 17 Chapter 4 Numerical Analysis of the MILP model 22 4.1 Experimental Design 22 4.2 Results Analysis 26 4.3 Cost Parameter Sensitivity Analysis 29 Chapter 5 Cost Savings Allocation Problem 31 5.1 No Pre-set Rules 31 5.2 Proportional to Customer Demand 33 5.3 The Shapley Value 35 Chapter 6 Conclusions 37 Bibliography 39 국문초록 42석

Best matching processes in distributed systems

The growing complexity and dynamic behavior of modern manufacturing and service industries along with competitive and globalized markets have gradually transformed traditional centralized systems into distributed networks of e- (electronic) Systems. Emerging examples include e-Factories, virtual enterprises, smart farms, automated warehouses, and intelligent transportation systems. These (and similar) distributed systems, regardless of context and application, have a property in common: They all involve certain types of interactions (collaborative, competitive, or both) among their distributed individuals—from clusters of passive sensors and machines to complex networks of computers, intelligent robots, humans, and enterprises. Having this common property, such systems may encounter common challenges in terms of suboptimal interactions and thus poor performance, caused by potential mismatch between individuals. For example, mismatched subassembly parts, vehicles—routes, suppliers—retailers, employees—departments, and products—automated guided vehicles—storage locations may lead to low-quality products, congested roads, unstable supply networks, conflicts, and low service level, respectively. This research refers to this problem as best matching, and investigates it as a major design principle of CCT, the Collaborative Control Theory. The original contribution of this research is to elaborate on the fundamentals of best matching in distributed and collaborative systems, by providing general frameworks for (1) Systematic analysis, inclusive taxonomy, analogical and structural comparison between different matching processes; (2) Specification and formulation of problems, and development of algorithms and protocols for best matching; (3) Validation of the models, algorithms, and protocols through extensive numerical experiments and case studies. The first goal is addressed by investigating matching problems in distributed production, manufacturing, supply, and service systems based on a recently developed reference model, the PRISM Taxonomy of Best Matching. Following the second goal, the identified problems are then formulated as mixed-integer programs. Due to the computational complexity of matching problems, various optimization algorithms are developed for solving different problem instances, including modified genetic algorithms, tabu search, and neighbourhood search heuristics. The dynamic and collaborative/competitive behaviors of matching processes in distributed settings are also formulated and examined through various collaboration, best matching, and task administration protocols. In line with the third goal, four case studies are conducted on various manufacturing, supply, and service systems to highlight the impact of best matching on their operational performance, including service level, utilization, stability, and cost-effectiveness, and validate the computational merits of the developed solution methodologies

Inventory management with advance capacity information

One of the important aspects of supply chain management is dealing with demand and supply uncertainty. The uncertainty of future supply can be reduced, if a company is able to obtain advance capacity information (ACI) on future supply/production capacity availability from its supplier. We address a periodic-review inventory system under stochastic demand and stochastic limited supply, for which ACI is available. We show that the optimal ordering policy is a state-dependent base stock policy characterized by a base stock level that is a function of ACI. We establish a link to inventory models using advance demand information (ADI) by developing a capacitated inventory system with ADI, and showing that the model is closely related to the proposed ACI model. Our numerical results reveal several managerial insights. In particular, we show that ACI is most beneficial when there exists sufficient flexibility to react to anticipated demand and supply capacity mismatches. Further, most of the benefits can be reached with only limited future visibility. We also show that the system parameters affecting the value of ACI interact in a complex way, and therefore need to be considered in an integrated manner

An ESPC algorithm based approach to solve inventory deployment problem

Global competitiveness has enforced the hefty industries to become more customized. To compete in the market they are targeting the customers who want exotic products, and faster and reliable deliveries. Industries are exploring the option of satisfying a portion of their demand by converting strategically placed products, this helps in increasing the variability of product produced by them in short lead time. In this paper, authors have proposed a new hybrid evolutionary algorithm named Endosymbiotic-Psychoclonal (ESPC) algorithm to determine the amount and type of product to stock as a semi product in inventory. In the proposed work the ability of previously proposed Psychoclonal algorithm to exploit the search space has been increased by making antibodies and antigen more cooperative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results obtained, are compared with other evolutionary algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained, and convergence time required to reach the optimal /near optimal value of the solution

Assessment of joint inventory replenishment: a cooperative games approach

This research deals with the design of a logistics strategy with a collaborative approach between non-competing companies, who through joint coordination of the replenishment of their inventories reduce their costs thanks to the exploitation of economies of scale. The collaboration scope includes sharing logistic resources with limited capacities; transport units, warehouses, and management processes. These elements conform a novel extension of the Joint Replenishment Problem (JRP) named the Schochastic Collaborative Joint replenishment Problem (S-CJRP). The introduction of this model helps to increase practical elements into the inventory replenishment problem and to assess to what extent collaboration in inventory replenishment and logistics resources sharing might reduce the inventory costs. Overall, results showed that the proposed model could be a viable alternative to reduce logistics costs and demonstrated how the model can be a financially preferred alternative than individual investments to leverage resources capacity expansions. Furthermore, for a practical instance, the work shows the potential of JRP models to help decision-makers to better understand the impacts of fleet renewal and inventory replenishment decisions over the cost and CO2 emissions.DoctoradoDoctor en Ingeniería Industria